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https://bokeh.github.io/colorcet
A set of useful perceptually uniform colormaps for plotting scientific data
https://bokeh.github.io/colorcet
bokeh colorcet colormaps holoviz matplotlib plotly
Last synced: 28 days ago
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A set of useful perceptually uniform colormaps for plotting scientific data
- Host: GitHub
- URL: https://bokeh.github.io/colorcet
- Owner: holoviz
- License: other
- Created: 2016-11-07T03:30:57.000Z (about 8 years ago)
- Default Branch: main
- Last Pushed: 2024-09-10T07:03:51.000Z (3 months ago)
- Last Synced: 2024-11-11T16:41:56.299Z (about 1 month ago)
- Topics: bokeh, colorcet, colormaps, holoviz, matplotlib, plotly
- Language: Python
- Homepage: http://colorcet.holoviz.org
- Size: 12.6 MB
- Stars: 689
- Watchers: 16
- Forks: 54
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-open-geoscience - Colorcet
README
-----------------
# Colorcet: Collection of perceptually uniform colormaps
| | |
| --- | --- |
| Build Status | [](https://github.com/holoviz/colorcet/actions/workflows/tests.yaml?query=branch%3Amain) |
| Coverage | [](https://codecov.io/gh/holoviz/colorcet) ||
| Latest dev release | [](https://github.com/holoviz/colorcet/tags) [](https://holoviz-dev.github.io/colorcet/) |
| Latest release | [](https://github.com/holoviz/colorcet/releases) [](https://pypi.python.org/pypi/colorcet) [](https://anaconda.org/holoviz/colorcet) [](https://anaconda.org/conda-forge/colorcet) [](https://anaconda.org/anaconda/colorcet) |
| Python | [](https://pypi.org/project/colorcet/) |
| Docs | [](https://github.com/holoviz/colorcet/tree/gh-pages) [](http://colorcet.holoviz.org) |
## What is it?
Colorcet is a collection of
perceptually uniform colormaps for use with Python plotting programs like
[bokeh](http://bokeh.pydata.org),
[matplotlib](http://matplotlib.org),
[holoviews](http://holoviews.org), and
[datashader](https://github.com/bokeh/datashader) based on the
set of [perceptually uniform colormaps](https://arxiv.org/abs/1509.03700) created
by Peter Kovesi at the Center for Exploration Targeting.
## Installation
Colorcet supports Python 3.7 and greater on Linux, Windows, or Mac
and can be installed with conda:
```sh
conda install colorcet
```
or with pip:
```sh
python -m pip install colorcet
```
To work with JupyterLab you will also need the PyViz JupyterLab extension:
```sh
conda install -c conda-forge jupyterlab
jupyter labextension install @pyviz/jupyterlab_pyviz
```
Once you have installed JupyterLab and the extension launch it with:
```sh
jupyter-lab
```
If you want to try out the latest features between releases, you can get the latest dev release by installing:
```sh
conda install -c pyviz/label/dev colorcet
```
For more information take a look at [Getting Started](http://colorcet.holoviz.org/getting_started).
## Learning more
You can see all the details about the methods used to create these
colormaps in [Peter Kovesi's 2015 arXiv
paper](https://arxiv.org/pdf/1509.03700v1.pdf). Other useful
background is available in a [1996 paper from
IBM](http://www.research.ibm.com/people/l/lloydt/color/color.HTM).
The Matplotlib project also has a number of relevant resources,
including an excellent
[2015 SciPy talk](https://www.youtube.com/watch?v=xAoljeRJ3lU), the
[viscm tool for creating maps like the four in mpl](https://github.com/matplotlib/viscm), the
[cmocean site](http://matplotlib.org/cmocean/) collecting a set of maps created by viscm,
and the [discussion of how the mpl maps were created](https://bids.github.io/colormap/).
## Samples
Some of the Colorcet colormaps that have short, memorable names (which are probably
the most useful ones) are visible here:
But the complete set of 100+ is shown in the [User Guide](http://colorcet.holoviz.org/user_guide).